The future of life sciences is connected, AI-driven, and patient-centric

The future of life sciences will likely be shaped by tech-enabled connectivity, strategic uses of AI, and patient-centric supply chains.

The future of life sciences will likely be shaped by tech-enabled connectivity, ....


Today's expectations for life sciences companies include faster innovation, transparent drug pricing, and a larger purpose beyond profits. Some businesses are hunkering down to weather the economic storm. Leaders, on the other hand, are rethinking their operating models to meet stakeholder expectations, anticipate threats, and capitalize on data-driven insights to win in the marketplace.

In the latest report, The Future of Life Sciences, KPMG professionals examine four primary signs of change and four strategic imperatives that represent the future of life sciences.

Signals of change

1. Precision medicine changes the game.

The life sciences industry has made major breakthroughs in precision medicine, which comprises treatments tailored to individuals' unique genetic profiles and, in some cases, engineers a therapy from a patient's own cells. The key drivers are multiomic technologies which combine genomics, proteomics, and metabolomics-based diagnostics into one holistic picture of a patient, drawing on data from the whole body. While not all clinical diagnostics laboratories have the platforms to do this work, the industry is striving to overcome access challenges through meaningful connections between diagnostics and life science tool companies, testing centers, and reference labs. Scaling precision medicine will require more than just increasing manufacturing capacity and furnishing clinical labs with new technologies. It requires connection and coordination across a variety of functions. As precision medicine continues to advance, manufacturers will be evaluated not only on therapy efficacy, but also on their ability to seamlessly connect with Healthcare Providers (HCPs) marking a significant shift towards integration into the patient care continuum.

2. Digital health alters the landscape

While digital health has been a topic in healthcare media for nearly a decade, life sciences companies are now breathing new life into existing technologies and introducing new innovations at a breathtaking pace. The convergence of enormous bandwidth, widespread smartphone adoption, and increased digital fluency is driving explosive growth in digital health offerings, addressing the rising expectations of consumers for better-connected healthcare experiences. The workforce landscape is shifting, with Generations X, Y, and Z constituting 75 percent, and the digital-native Y and Z generations show a preference for tailored connected experiences. With the burden of cost shifting to the individual, patients are taking more active roles in their own care with fitness devices, wellness apps, and easily accessible information online. Recognizing the potential of digital health tools to enhance workflow efficiency and extend geographical reach, healthcare providers are seeking easy and convenient access to information and tools to connect with patients and improve their clinical outcomes. Well-funded startups and tech giants are contributing expertise in connected infrastructure, advanced analytics, and user experience. Medical device companies are rebranding themselves as 'MedTech' and pharmaceutical companies are investing and forging digital health partnerships to supplement and differentiate their core therapies. Common criteria for innovative solutions include engaging user experiences, seamless integration, secure data, and real-time connectivity. 

3. Artificial intelligence and machine learning are everywhere.

Artificial Intelligence (AI) and Machine Learning (ML) have gone from novel experiments to the top of the C-suite agenda across most industries. Life sciences has been ahead by using AI in research and development, and decision support long before the current AI excitement. In the medical technology sector, ML has helped them realize accelerated cycle times, cost reduction, and improved quality in device and diagnostics development, resulting the most future growth potential in connected digital health. AI's role in drug research process is allowing pharmaceutical companies to enhance discovery and innovation, connect with potential clinical trial participants worldwide, bring therapies to market faster, and shorten the time to realize return on investment (ROI) on new drugs. However, getting full value out of AI tools demands robust data curation and an evolution of the extended operating model. In other words, “becoming digital” requires transformation beyond algorithms to include the operational processes and skills that can change “how work gets done”. Although, technology advances such as AI and ML, as well as smart devices and digitalization of the supply chain, are critical to the growth and resiliency of the industry, this level of level of connectivity also introduces new security risks. There are both government-and industry-led efforts advocating for increased governance and oversight to ensure that AI algorithms are unbiased, patient data is secured, and solutions don’t create cybersecurity vulnerabilities. 

4. Critical risks persist: Supply chain disruption, cyber breaches, and counterfeiting.

The pandemic shed light to the vulnerability of the life sciences supply chain to disruption, which caused shortages of essential medications. However, the shortages happened before that. In 2019 a U.S. Senate study identified concerning gaps in supply chain insight and the pervasive inability to trace sources of supply. The ability to forecast and avoid or mitigate shortages depends on accurate data. Therefore, greater transparency is needed into supplier operations, which will require substantial investments in data integration and data protection. The life sciences supply chain is also vulnerable to both cyber threats and counterfeit products. Patient data held by life sciences companies is particularly susceptible to cyber-theft as this data purportedly sells on the black market for more than financial data. Compounding the problem is the increased dependence on third-party suppliers with varying degrees of cyber maturity. Counterfeiting issues worsened during the pandemic as bad actors seized the opportunity of the huge spike in demand for drugs and medical equipment particularly in emerging markets. 

Four Strategic Imperatives

1. Design tech-enabled, customer-centric experiences

Life sciences industry has adopted customer relationship management (CRM) technologies the earliest, but it is among the furthest behind in putting the customer at the center of its decision-making. There’s a critical need to deliver intentional, connected interactions to meet the needs of the industry’s three key stakeholders—payers, providers, and patients. The focus is on delivering a great user experience, appropriate products, services, and information tailored to each stakeholder in an accessible and sustainable solutions.

  • Payer communications must center around value—not just for the payer, but for the patient and broader society. Value propositions for new products, including digital health solutions, should be supported by compelling data and insights.
  • Healthcare providers (HCPs) are facing post-pandemic stress, staff shortages, supply chain disruptions, and increased demand from patients and health care systems. Life sciences companies should be mindful of these stressors and endure that the products and services they offer lessen HCPs’ burden instead of adding to it.
  • Patients need to be at the center of all life sciences decisions. Developing a patient journey map is an effective way to understand the patient experience, and life sciences companies should position themselves as a conduit between healthcare providers and patients to help patients manage their health and ensure they have exceptional care experiences. Sophisticated smart devices empower patients and caregivers to connect to each other leading a trend toward platform-based ecosystems (PBE) that offer omni-channel experiences allowing real-time troubleshooting, tailored content delivery, personalized products and services, tele-health services, and patient support. The omni-channel has expanded as customers expect touchpoints across various channels including the transforming channel such as AI-enabled chatbots that support patient screening, basic chat FAQ handling, and addressing procedure backlogs by separating care pathways.

2. Develop AI partnerships for faster time to market

The timeline for maximizing the return on investment for new innovative products has shrunk dramatically. Life sciences companies seeking competitive advantage need to be more decisive and nimbler than competitors from drug development to market entry in this fast-paced environment. Life sciences companies are forging partnerships with a range of AI companies, from focused startups to Big Tech. These firms can help predict optimal drug responses, identify suitable candidates and doses for clinical trials, reveal virus genomics, accelerate the analysis of clinical trial data, and ultimately support speed to market. This is not to say that other advanced technologies will be completely eclipsed by AI; robotic automation and ML models will continue to be used for applications, and we still do not see a future where laboratory-based science is completely eliminated. 

3. Rethink the supply chain

From enabling a more connected, personalized customer experience, to supporting novel therapeutics and precision medicine, to finding ways to mitigate the risk of disruption, there are many reasons that transforming the supply chain has moved to the top of the life sciences agenda.

  • The connected supply chain: Life sciences companies that invest in transforming their supply chains should do so with the goal of creating a dynamic, interconnected healthcare ecosystem to enable a more personalized patient experience. In the future, we envision an autonomous supply chain that self-learns, adapts, and focuses on continuously meeting the needs of value-chain customers, patients, and caregivers, while driving cost efficiencies and top-line growth. Data will be central to future supply chains, giving leaders a 360-degree view of their customers and other value chain participants.
  • Delivering on the promise of precision medicine: Pharmaceutical supply chain networks traditionally optimized for consistent, mass-market demand are increasingly being tasked with delivering precision medicine. Embracing precision medicine requires a shift to producing low-volume, highly personalized, high-value products in a ‘make-to-order’ model. Supply chain strategies must evolve, and new capabilities must be developed and executed at speed by creating digitally enabled operating model to manage complexities and cross-functional connectivity and collaboration for a deep understanding of patients and their health conditions.
  • Supply chain disruption: Life sciences companies should rethink existing operating models to improve supply chain resilience and continuity by considering the sufficient diversification to withstand disruption. The organizations need to be more agile so they can make rapid adjustments to production levels, shift to alternate suppliers, and reroute shipments, when necessary. More specifically, it is becoming increasingly critical to rethink supplier strategies and collaboration, diversify and segment the supplier base, strengthen connections with top suppliers, institute intelligent platforms to quickly onboard new partners, and explore reshoring and onshoring.

4. Manage Cyber Risks

  • Understand the risks associated with digital and emerging technologies. While digital and emerging technologies such as AI, ML, cloud, and the Industrial Internet of Things (IIoT) can enhance manufacturing productivity and visibility, they introduce a new spectrum of cybersecurity risks, and exponentially increase the attack surface. To get full value from these technologies, life sciences organizations should institute more robust access-management protocols, engage with procurement during initial vendor discussions to identify potential risks and collaborate on appropriate adjustments, and educate the business on the value of evaluating and pressure testing products early in the technology integration process so the cyber team can institute compensating controls.
  • Take responsibility for third-party risk. Since many life sciences suppliers are small businesses, they often lack investment in robust cybersecurity programs. Life sciences companies should ensure they conduct a thorough due diligence process before partnering with new suppliers. Third-party risk management (TPRM) programs should specify the controls, systems, platforms, and security protocols approved suppliers must have in place. If third parties are reluctant to commit to adopting cybersecurity protocols, then life sciences companies should consider whether changing vendors is warranted.

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